Identifying model inaccuracies and solution uncertainties in noninvasive activation-based imaging of cardiac excitation using convex relaxation. Erem, B., van Dam, P., & Brooks, D. IEEE Trans Med Imaging, 33(4):902–912, Apr, 2014. bibtex @Article{RSM:Ere2014,
author = "B. Erem and P.M. van Dam and D.H. Brooks",
title = "Identifying model inaccuracies and solution uncertainties
in noninvasive activation-based imaging of cardiac
excitation using convex relaxation.",
journal = "IEEE Trans Med Imaging",
year = "2014",
month = "Apr",
volume = "33",
number = "4",
pages = "902--912",
robnote = "Noninvasive imaging of cardiac electrical function has
begun to move towards clinical adoption. Here, we consider
one common formulation of the problem, in which the goal
is to estimate the spatial distribution of electrical
activation times during a cardiac cycle. We address the
challenge of understanding the robustness and uncertainty
of solutions to this formulation. This formulation poses a
nonconvex, nonlinear least squares optimization problem.
We show that it can be relaxed to be convex, at the cost
of some degree of physiological realism of the solution
set, and that this relaxation can be used as a framework
to study model inaccuracy and solution uncertainty. We
present two examples, one using data from a healthy human
subject and the other synthesized with the ECGSIM software
package. In the first case, we consider uncertainty in the
initial guess and regularization parameter. In the second
case, we mimic the presence of an ischemic zone in the
heart in a way which violates a model assumption. We show
that the convex relaxation allows understanding of spatial
distribution of parameter sensitivity in the first case,
and identification of model violation in the second.",
bibdate = "Sun Apr 10 19:47:10 2016",
pmcid = "PMC3982205",
}
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